1. Field of the Disclosure
The present innovation relates generally to parallel distributed computer systems for simulating neuronal networks that perform neural computations, such as visual perception and motor control.
2. Description of Related Art
Artificial spiking neural networks may be used to process signals, to gain an understanding of biological neural networks, and for solving artificial intelligence problems. These networks typically may employ a pulse-coded mechanism, which encodes information using timing of the pulses. Such pulses (also referred to as “spikes” or ‘impulses’) are short-lasting (typically on the order of 1-2 ms) discrete temporal events. Several exemplary implementations of such encoding are described in commonly owned and co-pending U.S. patent application Ser. No. 13/152,084 entitled APPARATUS AND METHODS FOR PULSE-CODE INVARIANT OBJECT RECOGNITION”, filed Jun. 2, 2011, and U.S. patent application Ser. No. 13/152,119, Jun. 2, 2011, entitled “SENSORY INPUT PROCESSING APPARATUS AND METHODS”, each incorporated herein by reference in its entirety.
Some existing approaches, such as described in co-owned U.S. patent application Ser. No. 13/239,123, filed Sep. 21, 2011 and entitled “ELEMENTARY NETWORK DESCRIPTION FOR NEUROMORPHIC SYSTEMS”, incorporated supra, utilize Elementary Network Description (END) framework in order to describe and simulate large-scale neuronal models using parallelized processing.
Some existing END implementations may utilize multi-compartment neurons and/or junctions. However, junctions may require to be operated using clock-based update rules (e.g., cyclic updates). Junctions may be provided with access to pre-synaptic network parameters in order to facilitate data communication between pre-synaptic and post-synaptic sides of the junction. As a result, cyclic updates of a network with junctions may become computationally intensive as described in U.S. patent application Ser. No. 13/239,259, filed Sep. 21, 2011 and entitled “APPARATUS AND METHODS FOR PARTIAL EVALUATION OF SYNAPTIC UPDATES BASED ON SYSTEM EVENTS”, incorporated supra.